Data Scientist

Brooklyn, New York, United States · Engineering


Company Overview:

Nearpod, recently named EdTech Digest’s Company of the Year, is the most comprehensive Student Engagement Platform for K-12 teachers. Nearpod works with any classroom technology from tablets and smartphones to laptops and Chromebooks to help engage students with activities such as Virtual Reality, PhET and Desmos and with more than 7,000 ready-to-run lessons created in partnership with leading brands like Common Sense Education and the Pulitzer Center. Beyond classroom instruction, the company revitalizes teacher development through teacher Professional Learning content that cultivates classroom-changing strategies for educators.

Since its launch in 2012, Nearpod has become a leader (& teacher favorite) in teaching and learning with technology. Currently teachers in 3 out of 5 districts in the US use Nearpod.

Nearpod has offices in Fort Lauderdale, FL and Brooklyn, NY, and is backed by notable investors like Insight Venture Partners, Reach Capital, Storm Ventures, the Stanford StartX Fund, and the Knight Enterprise Fund.

In 2019, Nearpod acquired Flocabulary, the leading video and student creativity platform that uses educational hip-hop to engage students and increase achievement. This acquisition has brought together two of the brands most loved by teacher to help engage students in all K-12 classrooms.

Location: Brooklyn, NY

Department: Tech

Position: Data Science Engineer

Position Overview:

As Nearpod’s Data Science Engineer, you are organized, analytical, and detail oriented with experience maintaining solid processes and data integrity. You are inquisitive and able to dive into the data to find answers to business problems. In this role, you'll be a key member of the team with an exciting startup with a strong social mission, and be in a position to make a significant positive impact on the business. You’ll help drive a wide range of projects.


About Analytics
We believe that good analytics help drive good business practices, and that the foundation is accurate data. The team is lean and is expected to be resourceful, thoughtful and creative when allocating resources, prioritizing, and solutioning.

Our stack consists of:



Key Traits:


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